Eclipse of the Public Corporation or Eclipse of the Public Markets?
Bibliographic record
Abstract
The authors look back at Michael Jensen's 1989 article “The Eclipse of the Public Corporation.” They find some of his predictions have been borne out but other important ones, not. Jensen concluded that the publicly held corporation was in decline and had outlived its usefulness in many sectors. He argued that agency costs made public corporations an inefficient form of organization and that new private organizational forms promoted by private equity firms would likely replace the public firm. The number of public firms in the U.S. has declined significantly but there are still many hugely profitable and successful public companies. U.S. public markets are still well‐suited for firms with mostly tangible assets. So, what we are really witnessing is an eclipse not of public corporations, but of the public markets as the place where young firms with mostly intangible capital seek their funding. This is especially true when the usefulness of the intangible assets has yet to be proven. Sometimes the market is extremely optimistic about some intangible assets, but otherwise firms with unproven intangible assets may be better off funding themselves privately. This evolution has a downside: investors limited to public markets are cut off from investing in high intangible‐asset firms. Additionally, as fewer firms remain publicly listed, fewer firms will be transparent to society.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.008 | 0.028 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".